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Market efficiency of Brazilian exchange rate: Evidence from variance ratio statistics and technical trading rules

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  • Tabak, Benjamin M.
  • Lima, Eduardo J.A.

Abstract

This study utilizes the variance ratio test to examine the behavior of Brazilian exchange rate. We show that adjustments for multiple tests and a bootstrap methodology must be employed in order to avoid size distortions. We propose a block bootstrap scheme and show that it has much nicer properties than the traditional Chow-Denning [Chow, K.V., Denning, K.C., 1993. A simple multiple variance ratio test. Journal of Econometrics 58 (3), 385-401] multiple variance ratio tests. Overall, the method proposed in the paper provides evidence refuting the random walk behavior for the Brazilian exchange rate for long investment horizon, but consistent with the random walk hypothesis for short-run horizon. Additionally, we also test for the predictive power of variable moving average (VMA) and trading range break (TRB) technical rules and find evidence of forecasting ability for these rules. Nonetheless, the excess return that can be obtained from such rules is not significant, suggesting that such predictability is not economically significant.

Suggested Citation

  • Tabak, Benjamin M. & Lima, Eduardo J.A., 2009. "Market efficiency of Brazilian exchange rate: Evidence from variance ratio statistics and technical trading rules," European Journal of Operational Research, Elsevier, vol. 194(3), pages 814-820, May.
  • Handle: RePEc:eee:ejores:v:194:y:2009:i:3:p:814-820
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    References listed on IDEAS

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    Cited by:

    1. Fahad Almudhaf, 2014. "Testing for random walk behaviour in CIVETS exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 21(1), pages 60-63, January.
    2. Yang, Jian & Cabrera, Juan & Wang, Tao, 2010. "Nonlinearity, data-snooping, and stock index ETF return predictability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 498-507, January.
    3. Victor Dragotă & Elena Ţilică, 2014. "Market efficiency of the Post Communist East European stock markets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 307-337, June.
    4. Vasilios Plakandaras & Theophilos Papadimitriou & Periklis Gogas & Konstantinos Diamantaras, 2014. "Market Sentiment and Exchange Rate Directional Forecasting," Working Paper series 37_14, Rimini Centre for Economic Analysis.
    5. Regis Augusto Ely, 2011. "Returns Predictability and Stock Market Efficiency in Brazil," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(4), pages 571-584.
    6. Todea, Alexandru & Zoicas Ienciu, Adrian, 2011. "Technical Analysis and Stochastic Properties of Exchange Rate Movements: Empirical Evidence from the Romanian Currency Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 175-192, March.
    7. Doyle, John R. & Chen, Catherine H., 2013. "Patterns in stock market movements tested as random number generators," European Journal of Operational Research, Elsevier, vol. 227(1), pages 122-132.
    8. Shyh-wei Chen, 2009. "Random walks in asian foreign exchange markets:evidence from new multiple variance ratio tests," Economics Bulletin, AccessEcon, vol. 29(2), pages 1296-1307.
    9. Lingras, P. & Butz, C.J., 2010. "Rough support vector regression," European Journal of Operational Research, Elsevier, vol. 206(2), pages 445-455, October.
    10. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.

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